An estimate of the planar motion of the ground can
be found by calculating the ego-motion of the vehicle based on the
fusion of CAN
bus readings with motion information from image features. This in turn can be compared to the motion from the
video sensors to detect objects that are not part of the ground.
This technique can be applied to all types of cameras and lenses.
Below are some results from this research.

Model-Based Surround Detection

For detecting vehicles to the side of the car, a
model-based wheel detector can be used. After de-warping the
omnidirectional image to generate a side view, a Gaussian Mixture Model
based probabilistic detection system is used to extract possible wheel
locations. These candidates are tracked and wheel position
estimates are further refined based on this tracking. Below are
some results from this research.

Videos of these results can be viewed in the
Videos portion of this
web site

More details on these research
topics can be viewed in the Publications
portion of this web site.